ReMe/examples/cli

The Cli Interface of MemoryScope

Usage

MemoryScope can be launched in two different ways:

1. Using YAML Configuration File

If you prefer to configure your settings via a YAML file, you can do so by providing the path to the configuration file as follows:

memoryscope --config_path=memoryscope/core/config/demo_config.yaml

2. Using Command Line Arguments

Alternatively, you can specify all the parameters directly on the command line:

# Chinese / Dashscope
memoryscope --language="cn" \
            --memory_chat_class="cli_memory_chat" \
            --human_name="用户" \
            --assistant_name="AI" \
            --generation_backend="dashscope_generation" \
            --generation_model="qwen-max" \
            --embedding_backend="dashscope_embedding" \
            --embedding_model="text-embedding-v2" \
            --enable_ranker=True \
            --rank_backend="dashscope_rank" \
            --rank_model="gte-rerank"
# English / OpenAI
memoryscope --language="en" \
            --memory_chat_class="cli_memory_chat" \
            --human_name="user" \
            --assistant_name="AI" \
            --generation_backend="openai_generation" \
            --generation_model="gpt-4o" \
            --embedding_backend="openai_embedding" \
            --embedding_model="text-embedding-3-small" \
            --enable_ranker=False

Here are the available options that can be set through either method:

• --language: The language used for the conversation.
• --memory_chat_class: The class name for managing the chat history.
• --human_name: The name of the human user.
• --assistant_name: The name of the AI assistant.
• --generation_backend: The backend used for generating responses.
• --generation_model: The model used for generating responses.
• --embedding_backend: The backend used for text embeddings.
• --embedding_model: The model used for creating text embeddings.
• --enable_ranker: A boolean indicating whether to use a dummy ranker (default is False).
• --rank_backend: The backend used for ranking responses.
• --rank_model: The model used for ranking responses.